Bibliographic record
Abstract
The identity of a group is captured in prototypical members who are perceived by members to embody the characteristics that define the group (Hogg, 1992; Tajfel & Turner, 1979). Of importance, the specific attributes of this group prototype can serve two functions. The first is to enhance perceived intragroup similarity if attributes of prototypes are common with other members, while the second is maximizing intergroup differences if attributes are more extreme. This study tested how different identity prototypes relate to the way individual members perceive the cohesiveness of the group. Team sport athletes (n = 102) were asked to think about the group member who best embodied the team (i.e., group prototype) and report the degree to which the member had qualities that were common/similar (commonalities) or extreme/superior (differences) to other team members. The individual attraction to the team (task and social) dimensions of group cohesion also were assessed. Results of a canonical correlation model, Wilks' ? = .82, F (4, 194) = 5.20, p = .001, indicated a significant amount of overlap in the variability of the prototype and cohesion variable sets accounting for 18% of the variance. When a group prototype was assessed as being common/similar to teammates, individual attraction to the group across task and social dimensions were higher. These findings provide preliminary evidence of a link between group prototype and team cohesion in sport and suggests that when the prototype features commonalities rather than differences between sport team members, task and social cohesion perceptions are higher.Acknowledgments: Social Science and Humanities Research Council of Canada Doctoral Scholarship to the first author (752-2014-2655)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".